Yinuo Zhao
Papers
2
Total Citations
16
H-Index
2
About
Yinuo Zhao is a leading researcher in robot learning and embodied intelligence, with a core focus on advancing multi-embodiment manipulation through large-scale, high-quality data. Their most impactful contribution is the creation of **RoboMIND (Multi-embodiment Intelligence Normative Data for Robot Manipulation)**, a landmark dataset that has garnered 16 total citations in just its first year. This resource provides 107,000 expert demonstration trajectories across 479 diverse tasks involving 96 object classes, collected via human teleoperation. By offering normative, standardized data for multiple robot platforms, Zhao’s work directly addresses the critical data scarcity bottleneck in generalist robot policy learning. The RoboMIND benchmark enables researchers to train and evaluate manipulation skills with unprecedented breadth and consistency, setting a new standard for reproducible research in the field. Zhao’s contributions are pivotal for scaling robot learning from narrow lab tasks to real-world, open-ended environments, making them a key figure in the push toward foundation models for physical intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2